The needs for fast sequence component retrieval and synchronization in power electronics and power engineering applications are numerous. Typical examples are: synchronization of inverters to an AC utility network, control of parallel connected inverters, synchronization of active filters, synchronization of line-commutated phase-controlled converters, synchronized signal processing, etc.
Sequence components are used in power systems and industrial applications to enable convenient examination and analysis of 3-phased power networks under both balanced and unbalanced operating conditions. Typical unbalances conditions are those caused by faults between the phases and/or ground, open phases and unbalanced loading such as static power equipment and single-phase devices.
The increasing use of static power devices has lead to many new applications of sequence components. For instance, in power conditioning equipment, the positive sequence component is needed for achieving a desired objective, e.g., unity power factor and constant output voltage, while the negative sequence component is required to compensate for current or voltage unbalance. The sequence components can be obtained through the use of a discrete transfer function.
The conventional symmetrical component method is used to extract sequence components where the base frequency is known a priori. Symmetrical components furnish significant insight into the behaviour of three-phase power networks and have been widely used in the fields of power system fault analysis and relaying protection. However, the use of the conventional method is inappropriate when the base frequency is not known a priori, which is generally the case. A partial solution to the problem involves continuously adapting the coefficients in the discrete transfer function. As the frequency changes, the coefficients are adapted and thus the discrete transfer function properties become frequency independent. This method, however, is computationally intensive. Furthermore, the time delay of two-thirds the period of the base signal caused by the traditional method has the disadvantage of causing delay and generating incorrect sequence components during input signal changes, because the data window spans the instant of signal change.
Another problem exists in obtaining reliable input signal data samples. When performing sequence extraction, the reliability of digital samples of a disturbed network signal can be limited by the performance of the digital bandpass filter. The predictive finite impulse response (FIR) and adaptive least mean square filtering approaches are widely used filtering techniques. Although these two types of filtering techniques are widely used in communications, motion control and power electronics, they still have some notable disadvantages. Predictive FIR filters require a high order for better harmonic attenuation resulting in a large look-up table for coefficients; generate considerable roundoff noise; and are sensitive to component parameter variations. The techniques for determining FIR filter coefficients are also complex. The drawbacks of LMS adaptive filters include a long transient response, extreme sensitivity to step-size parameters, and computational complexity.
Despite the drawbacks of the FIR and LMS filters, these filters were traditionally preferred over Infinite Impulse Response filters due to the latter's long transient response at high attenuation and possible instability due to pole placement and finite arithmetic.
The increasing application of nonlinear loads and devices in power systems has resulted in an increase in harmonics and disturbances in voltages and currents. This distortion causes several problems for metering, control and protective devices. Such problems include measurement errors, control system instability or relay misoperation. Metering, control and protective devices are basically designed to operate with fundamental sinusoidal components. Therefore, various filtering techniques are required to eliminate undesired frequencies. Traditional filters usually cause phase shift between the input signals and the output signals. This is problematic for power converters, where clear sinusoidal reference signals without phase shifting are required for synchronization or zero-crossing detection purposes.
From a power engineering or industrial electronics user perspective, there is a clear need for a signal-processing unit that can meet or be adapted to meet the following specifications:                Line frequency adaptation        Zero phase error between input and output signal under steady state conditions        Immunity to harmonic and aperiodic disturbances        Fast response to changes in the fundamental component in the presence of harmonic and aperiodic disturbances        Fast detection of a fault and or disturbance condition        
From a producer's perspective a suitable design should take the customer's functionality requirements into account subject to the additional constraint that the cost be acceptable. Cost is defined broadly to include product, training and integration costs. Directives that are conducive to lower costs include:                Small footprint area        Reduction of variable programming parameters        Appropriate partitioning of blocks that leads to a small number of blocks while retaining application flexibility        Reduction of analog trimming components        